Heparin is an effective treatment for preventing liver failure after hepatectomy.

BACKGROUND: Posthepatectomy liver failure (PHLF) is one of the most important causes of death following liver resection. Heparin, an established anticoagulant, can protect liver function through a number of mechanisms, and thus, prevent liver failure. AIM: To look at the safety and efficacy of heparin in preventing hepatic dysfunction after hepatectomy. METHODS: The data was extracted from Multiparameter Intelligent Monitoring in Intensive Care III (MIMIC-III) v1. 4 pinpointed patients who had undergone hepatectomy for liver cancer, subdividing them into two cohorts: Those who were injected with heparin and those who were not. The statistical evaluations used were unpaired t-tests, Mann-Whitney U tests, chi-square tests, and Fisher's exact tests to assess the effect of heparin administration on PHLF, duration of intensive care unit (ICU) stay, need for mechanical ventilation, use of continuous renal replacement therapy (CRRT), incidence of hypoxemia, development of acute kidney injury, and ICU mortality. Logistic regression was utilized to analyze the factors related to PHLF, with propensity score matching (PSM) aiming to balance the preoperative disparities between the two groups. RESULTS: In this study, 1388 patients who underwent liver cancer hepatectomy were analyzed. PSM yielded 213 matched pairs from the heparin-treated and control groups. Initial univariate analyses indicated that heparin potentially reduces the risk of PHLF in both matched and unmatched samples. Further analysis in the matched cohorts confirmed a significant association, with heparin reducing the risk of PHLF (odds ratio: 0.518; 95% confidence interval: 0.295-0.910; P = 0.022). Additionally, heparin treatment correlated with improved short-term postoperative outcomes such as reduced ICU stay durations, diminished requirements for respiratory support and CRRT, and lower incidences of hypoxemia and ICU mortality. CONCLUSION: Liver failure is an important hazard following hepatic surgery. During ICU care heparin administration has been proved to decrease the occurrence of hepatectomy induced liver failure. This indicates that heparin may provide a hopeful option for controlling PHLF.

MORTALITY RISK ASSESSMENT AMONG PATIENTS, HOSPITALIZED FOR COVID-19.

In Georgia, the number of confirmed cases of Coronavirus were 1,85,5289. Among them, 17 132 patients died. Information on risk factors for mortality is insufficient. The purpose of our research is to evaluate clinical features of heavy patients with severe COVID and determine prognostic factors of outcome. Factors associated with critical COVID-19 included older age and certain chronic medical conditions. The clinical material of 250 chronically ill COVID-19 patients admitted to the intensive care unit was retrospectively studied. We divided the patients into two groups. The dead and the survivors. Demographic data, comorbidities, chronic diseases, results of ultrasound, cardiography, computed tomography and laboratory characteristics were studied. In patients with chronic diseases, in the intensive care unit during COVID-19, the relative chance of survival decreases: CRP3 - OR=0.98(95% CI:0.97-0.99Hydrothorax- OR=0.24(95% CI:0.06-0.95); Sepsis/Septic shock - OR=0.07(95% CI:0.01-0.39); WBC - OR=0.86(95% CI:0.74-0.99); Mechanical lung ventilation - OR=0.01(95% CI:0.00-0.05)); increase survival relative chance- pO2 - OR=1.03(95% CI:1.0-1.06). Predictors of mortality in patients with chronic diseases: coagulation characteristics, inflammatory markers, sepsis, and artificial lung ventilation. Risk factors for covid-19 mortality need to be studied to increase pandemic preparedness.

Performance of the MRI lesion pattern score in predicting neurological outcome after out of hospital cardiac arrest: a retrospective cohort analysis.

BACKGROUND: Despite advances in resuscitation practice, patient survival following cardiac arrest remains poor. The utilization of MRI in neurological outcome prognostication post-cardiac arrest is growing and various classifications has been proposed; however a consensus has yet to be established. MRI, though valuable, is resource-intensive, time-consuming, costly, and not universally available. This study aims to validate a MRI lesion pattern score in a cohort of out of hospital cardiac arrest patients at a tertiary referral hospital in Switzerland. METHODS: This cohort study spanned twelve months from February 2021 to January 2022, encompassing all unconscious patients aged ≥ 18 years who experienced out-of-hospital cardiac arrest of any cause and were admitted to the intensive care unit (ICU) at Inselspital, University Hospital Bern, Switzerland. We included patients who underwent the neuroprognostication process, assessing the performance and validation of a MRI scoring system. RESULTS: Over the twelve-month period, 137 patients were admitted to the ICU, with 52 entering the neuroprognostication process and 47 undergoing MRI analysis. Among the 35 MRIs indicating severe hypoxic brain injury, 33 patients (94%) experienced an unfavourable outcome (UO), while ten (83%) of the twelve patients with no or minimal MRI lesions had a favourable outcome. This yielded a sensitivity of 0.94 and specificity of 0.83 for predicting UO with the proposed MRI scoring system. The positive and negative likelihood ratios were 5.53 and 0.07, respectively, resulting in an accuracy of 91.49%. CONCLUSION: We demonstrated the effectiveness of the MLP scoring scheme in predicting neurological outcome in patients following cardiac arrest. However, to ensure a comprehensive neuroprognostication, MRI results need to be combined with other assessments. While neuroimaging is a promising objective tool for neuroprognostication, given the absence of sedation-related confounders-compared to electroencephalogram (EEG) and clinical examination-the current lack of a validated scoring system necessitates further studies. Incorporating standardized MRI techniques and grading systems is crucial for advancing the reliability of neuroimaging for neuroprognostication. TRIAL REGISTRATION: Registry of all Projects in Switzerland (RAPS) 2020-01761.

Development and validation of a prediction model for mortality in critically ill COVID-19 patients.

Background: Early prediction of prognosis may help early treatment measures to reduce mortality in critically ill coronavirus disease (COVID-19) patients. The study aimed to develop a mortality prediction model for critically ill COVID-19 patients. Methods: This retrospective study analyzed the clinical data of critically ill COVID-19 patients in an intensive care unit between April and June 2022. Propensity matching scores were used to reduce the effect of confounding factors. A predictive model was built using logistic regression analysis and visualized using a nomogram. Calibration and receiver operating characteristic (ROC) curves were used to estimate the accuracy and predictive value of the model. Decision curve analysis (DCA) was used to examine the value of the model for clinical interventions. Results: In total, 137 critically ill COVID-19 patients were enrolled; 84 survived, and 53 died. Univariate and multivariate logistic regression analyses revealed that aspartate aminotransferase (AST), creatinine, and myoglobin levels were independent prognostic factors. We constructed logistic regression prediction models using the seven least absolute shrinkage and selection operator regression-selected variables (hematocrit, red blood cell distribution width-standard deviation, procalcitonin, AST, creatinine, potassium, and myoglobin; Model 1) and three independent factor variables (Model 2). The calibration curves suggested that the actual predictions of the two models were similar to the ideal predictions. The ROC curve indicated that both models had good predictive power, and Model 1 had better predictive power than Model 2. The DCA results suggested that the model intervention was beneficial to patients and patients benefited more from Model 1 than from Model 2. Conclusion: The predictive model constructed using characteristic variables screened using LASSO regression can accurately predict the prognosis of critically ill COVID-19 patients. This model can assist clinicians in implementing early interventions. External validation by prospective large-sample studies is required.

The paradox of workplace violence in the intensive care unit: a focus group study.

BACKGROUND: Conflicts with patients and relatives occur frequently in intensive care units (ICUs), driven by factors that are intensified by critical illness and its treatments. A majority of ICU healthcare professionals have experienced verbal and/or physical violence. There is a need to understand how healthcare professionals in ICUs experience and manage this workplace violence. METHODS: A qualitative descriptive analysis of four hospitals in Sweden was conducted using semi-structured focus-group interviews with ICU healthcare professionals. RESULTS: A total of 34 participants (14 nurses, 6 physicians and 14 other staff) were interviewed across the four hospitals. The overarching theme: "The paradox of violence in healthcare" illustrated a normalisation of violence in ICU care and indicated a complex association between healthcare professionals regarding violence as an integral aspect of caregiving, while simultaneously identifying themselves as victims of this violence. The healthcare professionals described being poorly prepared and lacking appropriate tools to manage violent situations. The management of violence was therefore mostly based on self-taught skills. CONCLUSIONS: This study contributes to understanding the normalisation of violence in ICU care and gives a possible explanation for its origins. The paradox involves a multifaceted approach that acknowledges and confronts the structural and cultural dimensions of violence in healthcare. Such an approach will lay the foundations for a more sustainable healthcare system.

Association between lactate/albumin ratio and prognosis in critically ill patients with acute kidney injury undergoing continuous renal replacement therapy.

BACKGROUND: The primary objective was to examine the association between the lactate/albumin ratio (LAR) and the prognosis of patients with acute kidney injury (AKI) undergoing continuous renal replacement therapy (CRRT). METHODS: Utilizing the Medical Information Mart for Intensive Care IV (MIMIC-IV, v2.0) database, we categorized 703 adult AKI patients undergoing CRRT into survival and non-survival groups based on 28-day mortality. Patients were further grouped by LAR tertiles: low (< 0.692), moderate (0.692-1.641), and high (> 1.641). Restricted cubic splines (RCS), Least Absolute Shrinkage and Selection Operator (LASSO) regression, inverse probability treatment weighting (IPTW), and Kaplan-Meier curves were employed. RESULTS: In our study, the patients had a mortality rate of 50.07% within 28 days and 62.87% within 360 days. RCS analysis revealed a non-linear correlation between LAR and the risk of mortality at both 28 and 360 days. Cox regression analysis, which was adjusted for nine variables identified by LASSO, confirmed that a high LAR (>1.641) served as an independent predictor of mortality at these specific time points (p < 0.05) in AKI patients who were receiving CRRT. These findings remained consistent even after IPTW adjustment, thereby ensuring a reliable and robust outcome. Kaplan-Meier survival curves exhibited a gradual decline in cumulative survival rates at both 28 and 360 days as the LAR values increased (log-rank test, χ2 = 48.630, p < 0.001; χ2 = 33.530, p < 0.001). CONCLUSION: A high LAR (>1.641) was found to be an autonomous predictor of mortality at both 28 and 360 days in critically ill patients with AKI undergoing CRRT.

Twenty percent human albumin solution fluid bolus administration therapy in patients after cardiac surgery-II: a multicentre randomised controlled trial.

PURPOSE: After cardiac surgery, fluid bolus therapy (FBT) with 20% human albumin may facilitate less fluid and vasopressor administration than FBT with crystalloids. We aimed to determine whether, after cardiac surgery, FBT with 20% albumin reduces the duration of vasopressor therapy compared with crystalloid FBT. METHODS: We conducted a multicentre, parallel-group, open-label, randomised clinical trial in six intensive care units (ICUs) involving cardiac surgery patients deemed to require FBT. We randomised 240 patients to receive up to 400 mL of 20% albumin/day as FBT, followed by 4% albumin for any subsequent FBT on that day, or to crystalloid FBT for at least the first 1000 mL, with use of crystalloid or 4% albumin FBT thereafter. The primary outcome was the cumulative duration of vasopressor therapy. Secondary outcomes included fluid balance. RESULTS: Of 480 randomised patients, 466 provided consent and contributed to the primary outcome (mean age 65 years; median EuroSCORE II 1.4). The cumulative median duration of vasopressor therapy was 7 (interquartile range [IQR] 0-19.6) hours with 20% albumin and 10.8 (IQR 0-22.8) hours with crystalloids (difference - 3.8 h, 95% confidence interval [CI] - 8 to 0.4; P = 0.08). Day one fluid balance was less with 20% albumin FBT (mean difference - 701 mL, 95% CI - 872 to - 530). CONCLUSIONS: In patients after cardiac surgery, when compared to a crystalloid-based FBT, 20% albumin FBT was associated with a reduced positive fluid balance but did not significantly reduce the duration of vasopressor therapy.

Relationship between admission blood urea nitrogen levels and postoperative length of stay in patients with hip fracture: A retrospective study.

To investigate the relationship between admission blood urea nitrogen (BUN) levels and postoperative length of stay (LOS) in hip fracture (HF) patients. This retrospective study retrieved related data from the MIMIC-IV database, of which the laboratory variables were taken preoperatively. The patients were divided into 4 groups according to the BUN quartile levels. After exploring the nonlinear relationship between BUN and LOS by generalized additive model, their connection was further analyzed using the generalized linear models, quantile regression models, and interaction analysis. Receiver operating characteristic curve analysis and decision curve analysis were performed to evaluate its value in predicting first intensive care unit admission and in-hospital mortality. Totally 1274 patients with HF were enrolled in the study. There was a nonlinear relationship between BUN and LOS (P < .05). Besides, BUN was an independent predictor for LOS after adjusting different covariates in 3 models (P < .05). Age served as a significant interactor in this relationship (P < .05). Moreover, receiver operating characteristic curve and decision curve analysis revealed the predictive value of BUN for intensive care unit admission and in-hospital mortality in HF. Admission BUN level as a cost-effective and easy-to-collect biomarker is significantly related to LOS in patients with HF. It helps clinicians to identify potential high-risk populations and take effective preventions before surgery to reduce postoperative LOS.

Factors associated with mortality of patients with COVID-19 on invasive mechanical ventilation: A retrospective cohort study in a university hospital in Northeastern Brazil.

The aim of this study is to identify the factors associated with mortality in patients with COVID-19 undergoing invasive mechanical ventilation at a university hospital in Northeastern Brazil. This is a retrospective cohort from April to August 2020 through an analysis of medical records, considering the demographic profile, comorbidities, complications, supports, respiratory and laboratory parameters. A total of 65 patients required invasive mechanical ventilation, of which 64.6% died in the ICU. They were older, had more comorbidities, shorter length of stay in the intensive care unit, received more support such as palliative care and two vasopressors simultaneously, showed lower levels of pH, hemoglobin and calcium, and higher levels of bicarbonate, lactate, prothrombin time, international normalized ratio, troponin and ferritin at the start of invasive mechanical ventilation. Furthermore, the time course of pH, arterial oxygen partial pressure to fractional inspired oxygen ratio, arterial carbon dioxide partial pressure, lactate, hemoglobin, platelets, lymphocytes, neutrophil-to-lymphocyte ratio, coagulation parameters, calcium, urea, aspartate aminotransferase, alanine aminotransferase, alkaline phosphatase, ferritin, static compliance, airway resistance, tidal volume, and noradrenaline doses showed association with mortality. There was a high mortality rate in invasively mechanically ventilated COVID-19 patients, with some associated factors identified at the start of invasive mechanical ventilation and others identified over time.

Analysis of factors associated with admission to the intensive care unit of children and adolescents with COVID-19: application of a multilevel model.

OBJECTIVE: To identify factors associated with hospitalization in the intensive care unit in children and adolescents with COVID-19. METHODS: This was a retrospective cohort study using secondary data of hospitalized children and adolescents (zero to 18 years old) with COVID-19 reported in Paraíba from April 2020 to July 2021, totaling 486 records. Descriptive analysis, logistic regression and multilevel regression were performed, utilizing a significance level of 5%. RESULTS: According to logistic regression without hierarchical levels, there was an increased chance of admission to the intensive care unit for male patients (OR = 1.98; 95%CI 1.18 - 3.32), patients with respiratory distress (OR = 2.43; 95%CI 1.29 - 4.56), patients with dyspnea (OR = 3.57; 95%CI 1.77 - 7.18) and patients living in large cities (OR = 2.70; 95%CI 1.07 - 6.77). The likelihood of requiring intensive care was observed to decrease with increasing age (OR = 0.94; 95%CI = 0.90 - 0.97), the presence of cough (OR = 0.32; 95%CI 0.18 - 0.59) or fever (OR = 0.42; 95%CI 0.23 - 0.74) and increasing Gini index (OR = 0.003; 95%CI 0.000 - 0.243). According to the multilevel analysis, the odds of admission to the intensive care unit increased in male patients (OR = 1.70; 95%CI = 1.68-1.71) and with increasing population size of the municipality per 100,000 inhabitants (OR = 1.01; 95%CI 1.01-1.03); additionally, the odds of admission to the intensive care unit decreased for mixed-race versus non-brown-skinned patients (OR = 0.981; 95%CI 0.97 - 0.99) and increasing Gini index (OR = 0.02; 95%CI 0.02 - 0.02). CONCLUSION: The effects of patient characteristics and social context on the need for intensive care in children and adolescents with SARS-CoV-2 infection were better estimated with the inclusion of a multilevel regression model.

Construction of a Risk Prediction Model for the Occurrence of Acute Skin Failure in Critically Ill Patients: A Prospective Study.

BACKGROUND: The risk factors for acute skin failure (ASF), a serious complication of the skin, are not fully understood. PURPOSE: This study was designed to explore the risk factors for ASF in critically ill patients and construct a clinical prediction model. METHODS: Intensive care unit patients were prospectively observed and assigned into two groups: with and without ASF. A logistic regression model was constructed, and its predictive power and clinical utility were evaluated. RESULTS: Of the 204 eligible patients enrolled as participants, 58 (28.43%) developed ASF. Sepsis, vasoactive drugs, and age were shown to be risk factors for ASF, whereas peripheral perfusion index ratio and albumin level were shown to be protective factors. The area under the receiver operating characteristic curve was 0.83. The maximum Youden index of the model was 0.39 (specificity: 0.87, sensitivity: 0.77). The Hosmer-Lemeshow test (p = .20) and calibration curve showed good fitness and predictive utility with respect to the model. CONCLUSIONS: The developed model effectively predicts ASF risk, allowing for the early identification of high-risk patients. Identifying risk factors such as sepsis, vasoactive drugs, and age and considering protective factors such as peripheral perfusion index and albumin levels may help optimize care plans. Clinical staff should pay special attention to these factors and their impact on skin health in critically ill patients.

Lymphocyte Levels and Morbidity and Mortality in Cardiovascular Surgery With Cardiopulmonary Bypass.

INTRODUCTION: A year ago, in a sample of 113 patients, our research group found that a high number of lymphocytes in the immediate postoperative period was correlated to a poor prognosis in cardiovascular surgeries. This study is an expansion of the initial study in order to confirm this finding. METHODS: We analyzed the data of 338 consecutive patients submitted to cardiovascular surgeries with cardiopulmonary bypass performed at Hospital Universitário Ciências Médicas (Belo Horizonte/Brazil) from 2015 to 2017. We analyzed 39 variables with the outcomes death, hospital stay, and intensive care unit stay. RESULTS: The value of lymphocytes in the immediate postoperative period > 2175.0/mm³ was an indicator of poor prognosis in this sample (P<0.001). The variables female sex, age, high level of European System for Cardiac Operative Risk Evaluation II, increased stay in the intensive care unit and in the ward, elevation of creatinine in the preoperative period and at intensive care unit discharge, elevation of the percentage of immediate postoperative period segmented neutrophils, high immediate postoperative period neutrophil/lymphocyte ratio, fasting hyperglycemia, preoperative critical condition, reintubation, mild or transient acute renal failure, surgical infection, cardiopulmonary bypass, and aortic cross-clamping and mechanical ventilation durations also had an impact on the mortality outcome. CONCLUSION: The value of lymphocytes in the immediate postoperative period > 2175.0/mm3 was an indicator of poor prognosis in cardiovascular surgery with cardiopulmonary bypass.

Sociodemographic Profile and Risk Factors for the Evolution of Patients with COVID-19 in ICUs in Brazil: A Cross-Sectional Study.

This is a cross-sectional study, with secondary data from Brazilian hospitals in the state of Paraíba, between January 2021 and January 2022. The evolution of clinical cases configured the dependent variable (cure or death), while the predictive variables were sociodemographic data, risk factors, use of ventilatory support, and vaccination against COVID-19. With the help of R software, the following tests were used: chi-square, Pearson's chi-square, and Fisher's exact adherence. Simple logistic regression models were constructed, and odds ratios (95% CI) were estimated using the LR test and Wald test. 7373 cases were reported, with a mean age of 58.1. Of the reported cases, 63.8% died. The most frequent sociodemographic profile included male people, of mixed race, with less than eight years of schooling. Chronic cardiovascular disease (OR 1.28; 95% CI: 1.13-1.45), diabetes (OR 1.41; 95% CI: 1.24-1.61), lung disease (OR 1.52; 95% CI: 1.11-2.09), and the use of invasive ventilatory support (OR 14.1; 95% CI: 10.56-18.59) were all associated with increased mortality. Nonvaccination was associated with a decreased risk of death (OR 0.74; 95% CI: 0.65-0.84). Male patients, nonwhite, and those with low education were more likely to have a worse clinical outcome. The risk factors studied were related to deaths, and those who did not require ventilatory support were related to cure.

Prevalence of mortality among mechanically ventilated patients in the intensive care units of Ethiopian hospitals and the associated factors: A systematic review and meta-analysis.

BACKGROUND: In the intensive care unit (ICU), mechanical ventilation (MV) is a typical way of respiratory support. The severity of the illness raises the likelihood of death in patients who require MV. Several studies have been done in Ethiopia; however, the mortality rate differs among them. The objective of this systematic review and meta-analysis is to provide a pooled prevalence of mortality and associated factors among ICU-admitted patients receiving MV in Ethiopian hospitals. METHODS: We used the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) 2020 criteria to conduct a comprehensive systematic review and meta-analysis in this study. We searched PubMed/Medline, SCOPUS, Embase, Hinari, and Web of Science and found 22 articles that met our inclusion criteria. We used a random-effects model. To identify heterogeneity within the included studies, meta-regression and subgroup analysis were used. We employed Egger's regression test and funnel plots for assessing publication bias. STATA version 17.0 software was used for all statistical analyses. RESULTS: In this systematic review and meta-analysis, the pooled prevalence of mortality among 7507 ICU-admitted patients from 22 articles, who received MV was estimated to be 54.74% [95% CI = 47.93, 61.55]. In the subgroup analysis by region, the Southern Nations, Nationalities, and Peoples (SNNP) subgroup (64.28%, 95% CI = 51.19, 77.37) had the highest prevalence. Patients with COVID-19 have the highest mortality rate (75.80%, 95% CI = 51.10, 100.00). Sepsis (OR = 6.85, 95%CI = 3.24, 14.46), Glasgow Coma Scale (GCS) score<8 (OR = 6.58, 95%CI = 1.96, 22.11), admission with medical cases (OR = 4.12, 95%CI = 2.00, 8.48), Multi Organ Dysfunction Syndrome (MODS) (OR = 2.70, 95%CI = 4.11, 12.62), and vasopressor treatment (OR = 19.06, 95%CI = 9.34, 38.88) were all statistically associated with mortality. CONCLUSION: Our review found that the pooled prevalence of mortality among mechanically ventilated ICU-admitted patients in Ethiopia was considerably high compared to similar studies in the United States (US), China, and other countries. Sepsis, GCS<8, medical cases, MODS, and use of vasopressors were statistically associated with mortality. Clinicians should exercise caution while mechanically ventilating ICU-admitted patients with these factors. However, it should be noted that the exact cause and effect relationship could not be established with this meta-analysis, as the available evidence is not sufficient. Thus, more studies using prospective methods will be required.

Development of machine learning models predicting mortality using routinely collected observational health data from 0-59 months old children admitted to an intensive care unit in Bangladesh: critical role of biochemistry and haematology data.

INTRODUCTION: Treatment in the intensive care unit (ICU) generates complex data where machine learning (ML) modelling could be beneficial. Using routine hospital data, we evaluated the ability of multiple ML models to predict inpatient mortality in a paediatric population in a low/middle-income country. METHOD: We retrospectively analysed hospital record data from 0-59 months old children admitted to the ICU of Dhaka hospital of International Centre for Diarrhoeal Disease Research, Bangladesh. Five commonly used ML models- logistic regression, least absolute shrinkage and selection operator, elastic net, gradient boosting trees (GBT) and random forest (RF), were evaluated using the area under the receiver operating characteristic curve (AUROC). Top predictors were selected using RF mean decrease Gini scores as the feature importance values. RESULTS: Data from 5669 children was used and was reduced to 3505 patients (10% death, 90% survived) following missing data removal. The mean patient age was 10.8 months (SD=10.5). The top performing models based on the validation performance measured by mean 10-fold cross-validation AUROC on the training data set were RF and GBT. Hyperparameters were selected using cross-validation and then tested in an unseen test set. The models developed used demographic, anthropometric, clinical, biochemistry and haematological data for mortality prediction. We found RF consistently outperformed GBT and predicted the mortality with AUROC of ≥0.87 in the test set when three or more laboratory measurements were included. However, after the inclusion of a fourth laboratory measurement, very minor predictive gains (AUROC 0.87 vs 0.88) resulted. The best predictors were the biochemistry and haematological measurements, with the top predictors being total CO2, potassium, creatinine and total calcium. CONCLUSIONS: Mortality in children admitted to ICU can be predicted with high accuracy using RF ML models in a real-life data set using multiple laboratory measurements with the most important features primarily coming from patient biochemistry and haematology.

High flow nasal cannula oxygen therapy versus non-invasive ventilation for acute exacerbations of chronic obstructive pulmonary disease with acute-moderate hypercapnic respiratory failure: a randomized controlled non-inferiority trial.

BACKGROUND: Although cumulative studies have demonstrated a beneficial effect of high-flow nasal cannula oxygen (HFNC) in acute hypercapnic respiratory failure, randomized trials to compare HFNC with non-invasive ventilation (NIV) as initial treatment in acute exacerbations of chronic obstructive pulmonary disease (AECOPD) patients with acute-moderate hypercapnic respiratory failure are limited. The aim of this randomized, open label, non-inferiority trial was to compare treatment failure rates between HFNC and NIV in such patients. METHODS: Patients diagnosed with AECOPD with a baseline arterial blood gas pH between 7.25 and 7.35 and PaCO2 ≥ 50 mmHg admitted to two intensive care units (ICUs) at a large tertiary academic teaching hospital between March 2018 and December 2022 were randomly assigned to HFNC or NIV. The primary endpoint was the rate of treatment failure, defined as endotracheal intubation or a switch to the other study treatment modality. Secondary endpoints were rates of intubation or treatment change, blood gas values, vital signs at one, 12, and 48 h, 28-day mortality, as well as ICU and hospital lengths of stay. RESULTS: 225 total patients (113 in the HFNC group and 112 in the NIV group) were included in the intention-to-treat analysis. The failure rate of the HFNC group was 25.7%, while the NIV group was 14.3%. The failure rate risk difference between the two groups was 11.38% (95% CI 0.25-21.20, P = 0.033), which was higher than the non-inferiority cut-off of 9%. In the per-protocol analysis, treatment failure occurred in 28 of 110 patients (25.5%) in the HFNC group and 15 of 109 patients (13.8%) in the NIV group (risk difference, 11.69%; 95% CI 0.48-22.60). The intubation rate in the HFNC group was higher than in the NIV group (14.2% vs 5.4%, P = 0.026). The treatment switch rate, ICU and hospital length of stay or 28-day mortality in the HFNC group were not statistically different from the NIV group (all P > 0.05). CONCLUSION: HFNC was not shown to be non-inferior to NIV and resulted in a higher incidence of treatment failure than NIV when used as the initial respiratory support for AECOPD patients with acute-moderate hypercapnic respiratory failure. TRIAL REGISTRATION: chictr.org (ChiCTR1800014553). Registered 21 January 2018, http://www.chictr.org.cn.

The pattern of antibiotic utilisation among intensive care unit patients hospitalised in a Gauteng (South African) provincial tertiary hospital: Comparing findings before and during COVID-19.

BACKGROUND: Various mechanisms may contribute to and direct the progression of antibiotic resistance. A prominent driver associated with antibiotic resistance is inappropriate use or consumption. The sudden emergence of coronavirus disease 2019 (COVID-19 ) changed the conventional practices related to antibiotic utilisation through repurposing the use of antibiotics. Apart from the implementation of antibiotic stewardship programmes, the pressure COVID-19 placed on healthcare systems resulted in poor prescribing and medication review practices, potentially exacerbating antibiotic resistance. Furthermore, the public health system has issues that make it difficult to routinely monitor, quantify antibiotic consumption, and offer evaluation, feedback and intervention, particularly in low- and middle- income countries such as South Africa (SA). Therefore, this study aimed to determine antibiotic utilisation before and during the COVID-19 pandemic in a Gauteng provincial tertiary hospital (GPTH) in SA. OBJECTIVE: To determine, examine, and compare antibiotic consumption among intensive care unit (ICU) patients admitted to a GPTH during the pre-COVID-19 period and during the COVID-19 pandemic, in addition to determining the prevalence of the World Health Organisation (WHO) 'watch' category antibiotics before and following the emergence of COVID-19 . METHODS: A retrospective cross-sectional data analysis was undertaken of 335 medical files of ICU patients hospitalised in a GPTH between January 2017 and December 2021. Descriptive statistics were used to examine patient characteristics and antibiotic prescribing variables (antibiotic selection, dosage, route of administration, frequency, duration of course and indication for which antibiotic was prescribed). RESULTS: The study found that the most frequently prescribed antibiotics were amoxicillin in combination with clavulanate (pre-pandemic 31.99%; amid-COVID-19 38.43%), followed by ceftriaxone (pre-pandemic 15.44%; amid-COVID-19 14.55%), piperacillin in combination with tazobactam (pre-pandemic 11.40%; amid-COVID-19 8.58%) and azithromycin (pre-pandemic 7.725%; amid-COVID-19 19.78%). CONCLUSION: The macrolide and penicillin (in combination with a beta-lactamase inhibitor) classes demonstrated an increase in consumption from the pre-pandemic period moving into the COVID-19 pandemic. This highlights the need for improved antibiotic stewardship programmes and policies to combat inappropriate and unnecessary antibiotic usage.

Prognostic value of serial (1,3)-ß-D-glucan measurements in ICU patients with invasive candidiasis.

BACKGROUND: To determine whether a decrease in serum (1,3)-ß-D-glucan (BDG) was associated with reduced mortality and to investigate the performance of BDG downslope in predicting clinical outcome in invasive candidiasis. METHODS: Observational cohort study in ICU patients over a ten-year period (2012-2022) in Italy. Proven invasive candidiasis with at least 2 BDG determinations were considered. RESULTS: In the study population of 103 patients (age 47 [35-62] years, SAPS II score 67 [52-77]) 68 bloodstream and 35 intrabdominal infections were recorded. Serial measurements showed that in 54 patients BDG decreased over time (BDG downslope group) while in 49 did not (N-BDG downslope group). Candida albicans was the pathogen most frequently isolated (61%) followed by C. parapsilosis (17%) and C. glabrata (12%), in absence of any inter-group difference. Invasive candidiasis related mortality was lower in BDG downslope than in N-BDG downslope group (17% vs 53%, p < 0.01). The multivariate Cox regression analysis showed the association of septic shock at infection occurrence and chronic liver disease with invasive candidiasis mortality (HR [95% CI] 3.24 [1.25-8.44] p = 0.02 and 7.27 [2.33-22.66] p < 0.01, respectively) while a BDG downslope was the only predictor of survival (HR [95% CI] 0.19 [0.09-0.43] p < 0.01). The area under the receiver operator characteristic curve for the performance of BDG downslope as predictor of good clinical outcome was 0.74 (p = 0.02) and our model showed that a BDG downslope > 70% predicted survival with both specificity and positive predictive value of 100%. CONCLUSIONS: A decrease in serum BDG was associated with reduced mortality and a steep downslope predicted survival with high specificity in invasive candidiasis.

Immune profiling of critically ill patients with acute kidney injury during the first week after various types of injuries: the REALAKI study.

BACKGROUND: Acute kidney injury (AKI) is common in hospitalized patients and results in significant morbidity and mortality. The objective of the study was to explore the systemic immune response of intensive care unit patients presenting with AKI, especially the association between immune profiles and persistent AKI during the first week after admission following various types of injuries (sepsis, trauma, surgery, and burns). METHODS: REALAKI is an ancillary analysis of the REAnimation Low Immune Status Marker (REALISM) cohort study, in which 359 critically ill patients were enrolled in three different intensive care units. Patients with end-stage renal disease were excluded from the REALAKI study. Clinical samples and data were collected three times after admission: at day 1 or 2 (D1-2), day 3 or 4 (D3-4) and day 5, 6 or 7 (D5-7). Immune profiles were compared between patients presenting with or without AKI. Patients with AKI at both D1-2 and D5-7 were defined as persistent AKI. A multivariable logistic regression model was performed to determine the independent association between AKI and patients' immunological parameters. RESULTS: Three hundred and fifty-nine patients were included in this analysis. Among them, 137 (38%) were trauma patients, 103 (29%) post-surgery patients, 95 (26%) sepsis patients, and 24 (7%) were burn patients. One hundred and thirty-nine (39%) patients presented with AKI at D1-2 and 61 (20%) at D5-7. Overall, 94% presented with persistent AKI at D5-7. Patients with AKI presented with increased pro and anti-inflammatory cytokines and altered innate and adaptive immune responses. The modifications observed in the immune profiles tended to be more pronounced with increasing KDIGO stages. In the logistic regression model, a statistically significant association was observed at D1-2 between AKI and CD10lowCD16low immature neutrophils (OR 3.03 [1.7-5.5]-p < 0.001). At D5-7, increased interleukin-10 (IL-10) levels and reduced ex vivo TNF-α production after LPS stimulation were significantly associated with the presence of AKI (OR 1.38 [1.12-1.71]-p = 0.001 and 0.51 [0.27-0.91]-p = 0.03, respectively). Patients who recovered from AKI between D1-2 and D5-7 compared to patients with persistent AKI at D5-7, tended to correct these alterations. CONCLUSION: Following various types of severe injuries, early AKI is associated with the initial inflammatory response. Presence of AKI at the end of the first week after injury is associated with injury-induced immunosuppression.